ArticleSleep science (Sao Paulo, Brazil)
Sleep physiological network analysis in children.
Article in Sleep science (Sao Paulo, Brazil). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 1 citations in OpenAlex.
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Authors and funding
4 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Objective: Physiological networks have recently been employed as an alternative to analyze the interaction of the human body. Within this option, different systems are analyzed as nodes inside a communication network as well how information fows. Several studies have been proposed to study sleep subjects with the help of the Granger causality computation over electroencephalographic and heart rate variability signals. However, following this methodology, novel approximations for children subjects are presented here, where comparison between adult and children sleep is followed through the obtained connectivities. Methods: Data from ten adults and children were retrospectively extracted from polysomnography records. Database was extracted from people suspected of having sleep disorders who participated in a previous study. Connectivity was computed based on Granger causality, according to preprocessing of similar studies in this feld. A comparison for adults and children groups with a chi-square test was followed, employing the results of the Granger causality measures. Results: Results show that differences were mainly established for nodes inside the brain network connectivity. Additionally, for interactions between brain and heart networks, it was brought to light that children physiology sends more information from heart to brain nodes compared to the adults group. Discussion: This study represents a frst sight to children sleep analysis, employing the Granger causality computation. It contributes to understand sleep in children employing measurements from physiological signals. Preliminary fndings suggest more interactions inside the brain network for children group compared to adults group.
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